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  2. Floating-point error mitigation - Wikipedia

    en.wikipedia.org/wiki/Floating-point_error...

    Variable length arithmetic represents numbers as a string of digits of a variable's length limited only by the memory available. Variable-length arithmetic operations are considerably slower than fixed-length format floating-point instructions.

  3. Pentium FDIV bug - Wikipedia

    en.wikipedia.org/wiki/Pentium_FDIV_bug

    Missing values in a lookup table used by the FPU's floating-point division algorithm led to calculations acquiring small errors. While these errors would in most use-cases only occur rarely and result in small deviations from the correct output values, in certain circumstances the errors can occur frequently and lead to more significant deviations.

  4. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    Round-to-nearest: () is set to the nearest floating-point number to . When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal to 0) is used.

  5. Numerical stability - Wikipedia

    en.wikipedia.org/wiki/Numerical_stability

    Even in this case, there is no guarantee that it would converge to the correct solution, because the floating-point round-off or truncation errors can be magnified, instead of damped, causing the deviation from the exact solution to grow exponentially.

  6. Guard digit - Wikipedia

    en.wikipedia.org/wiki/Guard_digit

    As an example, consider the subtraction . Here, the product notation indicates a binary floating point representation with the exponent of the representation given as a power of two and with the significand given with three bits after the binary point. To compute the subtraction it is necessary to change the forms of these numbers so that they ...

  7. Single-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Single-precision_floating...

    A floating-point variable can represent a wider range of numbers than a fixed-point variable of the same bit width at the cost of precision. A signed 32-bit integer variable has a maximum value of 2 31 − 1 = 2,147,483,647, whereas an IEEE 754 32-bit base-2 floating-point variable has a maximum value of (2 − 2 −23) × 2 127 ≈ 3.4028235 ...

  8. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    The following examples compute interval machine epsilon in the sense of the spacing of the floating point numbers at 1 rather than in the sense of the unit roundoff. Note that results depend on the particular floating-point format used, such as float , double , long double , or similar as supported by the programming language, the compiler, and ...

  9. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    A floating-point system can be used to represent, with a fixed number of digits, numbers of very different orders of magnitude — such as the number of meters between galaxies or between protons in an atom. For this reason, floating-point arithmetic is often used to allow very small and very large real numbers that require fast processing times.